Overview

Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare.

Full Product Details

Author:   Adam Bohr (Adam Bohr, PhD is the CEO and Co-founder of Sonohaler, Copenhagen, Denmark) ,  Kaveh Memarzadeh (Kaveh Memarzadeh, PhD is currently a Commercial Field Application Scientist at ChemoMetec, Lillerød, Denmark.)
Publisher:   Elsevier Science Publishing Co Inc
Imprint:   Academic Press Inc
Weight:   0.610kg
ISBN:  

9780128184387

ISBN 10:   0128184388
Pages:   378
Publication Date:   23 June 2020
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand  
We will order this item for you from a manufactured on demand supplier.

Table of Contents

List of contributors xi About the editors xiii Biographies xv Preface xxi Introduction xxiii 1. Current healthcare, big data, and machine learning 1 Adam Bohr and Kaveh Memarzadeh 1.1 Current healthcare practice 1 1.2 Value-based treatments and healthcare services 5 1.3 Increasing data volumes in healthcare 10 1.4 Analytics of healthcare data (machine learning and deep learning) 16 1.5 Conclusions/summary 21 References 22 2. The rise of artificial intelligence in healthcare applications 25 Adam Bohr and Kaveh Memarzadeh 2.1 The new age of healthcare 25 2.2 Precision medicine 28 2.3 Artificial intelligence and medical visualization 33 2.4 Intelligent personal health records 38 2.5 Robotics and artificial intelligence-powered devices 43 2.6 Ambient assisted living 46 2.7 The artificial intelligence can see you now 50 References 57 3. Drug discovery and molecular modeling using artificial intelligence 61 Henrik Bohr 3.1 Introduction. The scope of artificial intelligence in drug discovery 61 3.2 Various types of machine learning in artificial intelligence 64 3.3 Molecular modeling and databases in artificial intelligence for drug molecules 70 3.4 Computational mechanics ML methods in molecular modeling 72 3.5 Drug characterization using isopotential surfaces 74 3.6 Drug design for neuroreceptors using artificial neural network techniques 75 3.7 Specific use of deep learning in drug design 78 3.8 Possible future artificial intelligence development in drug design and development 80 References 81 4. Applications of artificial intelligence in drug delivery and pharmaceutical development 85 Stefano Colombo 4.1 The evolving pharmaceutical field 85 4.2 Drug delivery and nanotechnology 89 4.3 Quality-by-design R&D 92 4.4 Artificial intelligence in drug delivery modeling 95 4.5 Artificial intelligence application in pharmaceutical product R&D 98 4.6 Landscape of AI implementation in the drug delivery industry 109 4.7 Conclusion: the way forward 110 References 111 5. Cancer diagnostics and treatment decisions using artificial intelligence 117 Reza Mirnezami 5.1 Background 117 5.2 Artificial intelligence, machine learning, and deep learning in cancer 119 5.3 Artificial intelligence to determine cancer susceptibility 122 5.4 Artificial intelligence for enhanced cancer diagnosis and staging 125 5.5 Artificial intelligence to predict cancer treatment response 127 5.6 Artificial intelligence to predict cancer recurrence and survival 130 5.7 Artificial intelligence for personalized cancer pharmacotherapy 133 5.8 How will artificial intelligence affect ethical practices and patients? 136 5.9 Concluding remarks 137 References 139 6. Artificial intelligence for medical imaging 143 Khanhvi Tran, Johan Peter Bøtker, Arash Aframian and Kaveh Memarzadeh 6.1 Introduction 143 6.2 Outputs of artificial intelligence in radiology/medical imaging 144 6.3 Using artificial intelligence in radiology and overcoming its hurdles 146 6.4 X-rays and artificial intelligence in medical imaging—case 1 (Zebra medical vision) 151 6.5 Ultrasound and artificial intelligence in medical imaging—case 2 (Butterfly iQ) 156 6.6 Application of artificial intelligence in medical imaging—case 3 (Arterys) 158 6.7 Perspectives 160 References 161 7. Medical devices and artificial intelligence 163 Arash Aframian, Farhad Iranpour and Justin Cobb 7.1 Introduction 163 7.2 The development of artificial intelligence in medical devices 163 7.3 Limitations of artificial intelligence in medical devices 171 7.4 The future frontiers of artificial intelligence in medical devices 172 References 174 8. Artificial intelligence assisted surgery 179 Elan Witkowski and Thomas Ward 8.1 Introduction 179 8.2 Preoperative 179 8.3 Intraoperative 185 8.4 Postoperative 193 8.5 Conclusion 196 References 197 Further reading 202 9. Remote patient monitoring using artificial intelligence 203 Zineb Jeddi and Adam Bohr 9.1 Introduction to remote patient monitoring 203 9.2 Deploying patient monitoring 205 9.3 The role of artificial intelligence in remote patient monitoring 209 9.4 Diabetes prediction and monitoring using artificial intelligence 219 9.5 Cardiac monitoring using artificial intelligence 221 9.6 Neural applications of artificial intelligence and remote patient monitoring 224 9.7 Conclusions 229 References 230 10. Security, privacy, and information-sharing aspects of healthcare artificial intelligence 235 Jakub P. Hlávka 10.1 Introduction to digital security and privacy 235 10.2 Security and privacy concerns in healthcare artificial intelligence 237 10.3 Artificial intelligence’s risks and opportunities for data privacy 245 10.4 Addressing threats to health systems and data in the artificial intelligence age 253 10.5 Defining optimal responses to security, privacy, and information-sharing challenges in healthcare artificial intelligence 255 10.6 Conclusions 263 Acknowledgements 264 References 265 11. The impact of artificial intelligence on healthcare insurances 271 Rajeev Dutt 11.1 Overview of the global health insurance industry 271 11.2 Key challenges facing the health insurance industry 272 11.3 The application of artificial intelligence in the health insurance industry 274 11.4 Case studies 280 11.5 Moral, ethical, and regulatory concerns regarding the use of artificial intelligence 280 11.6 The limitations of artificial intelligence 282 11.7 The future of artificial intelligence in the health insurance industry 289 References 290 12. Ethical and legal challenges of artificial intelligence-driven healthcare 295 Sara Gerke, Timo Minssen and Glenn Cohen 12.1 Understanding “artificial intelligence” 296 12.2 Trends and strategies 296 12.3 Ethical challenges 300 12.4 Legal challenges 306 12.5 Conclusion 327 Acknowledgements 328 References 329 Concluding remarks 337 Index 339

Reviews

This book is overall a very complete and organized book that gives newly interested persons a look at AI and its applications. The first few chapters give readers a chance to get used to the vocabulary and give small but effective diagrams explaining often confused concepts such as machine learning versus deep learning. The first few chapters may be extremely dry if the readers are fairly familiar with AI. Therefore, I would recommend this book for readers who feel unsure of their foundation in AI. I would say of the books I have read on digital health in general, this book is more focused. If you compare to Data Pulse: A Brief Tour of Artificial Intelligence in Healthcare, Marcetich (New Degree Press, 2020) or Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again, Topal (Basic Books, 2019), both put a focus on challenges of AI, whereas this book has a large focus on the opportunities and covers them in great detail. --Doody Reviews

"""This book is overall a very complete and organized book that gives newly interested persons a look at AI and its applications. The first few chapters give readers a chance to get used to the vocabulary and give small but effective diagrams explaining often confused concepts such as machine learning versus deep learning. The first few chapters may be extremely dry if the readers are fairly familiar with AI. Therefore, I would recommend this book for readers who feel unsure of their foundation in AI. I would say of the books I have read on digital health in general, this book is more focused. If you compare to Data Pulse: A Brief Tour of Artificial Intelligence in Healthcare, Marcetich (New Degree Press, 2020) or Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again, Topal (Basic Books, 2019), both put a focus on challenges of AI, whereas this book has a large focus on the opportunities and covers them in great detail."" --Doody Reviews"

Author Information

Adam Bohr, PhD is the CEO and co-founder of Sonohaler, an mhealth and medical device company focused on asthma management using acoustic signals and machine learning tools. He is also a co-founder of Zerion ApS, a pharmaceutical company aspiring to transform the pharmaceutical landscape for formulation of poorly soluble drugs. Previously, he was employed as assistant professor at the Department of Pharmacy, University of Copenhagen where he was doing research on drug implants, nanomedicine and microfluidic technology and teaching pharmaceutical technology subjects. He has published more than 45 peer reviewed academic papers and book chapters and has a PhD in Biomedical Engineering from University College London. He is a health futurist and a healthcare AI proponent with a passion for patient centered healthcare technologies. Kaveh Memarzadeh, PhD is currently a Commercial Field Application Scientist at ChemoMetec, a biotechnology company that innovates in the field of automated cell cytometry. He oversaw research management and communications at Orthopaedic Research UK (ORUK), a UK based medical charity that funds projects into the betterment and improvement of human movement and augmentation. He has published numerous peer-reviewed academic papers and has a PhD in nanotechnology, biomaterials and microbiology. He is also a visiting lecturer at University College London, teaching on a range of topics from the future of prosthetics/bionics to utilization of nanotechnology for antimicrobial bone implants. In his spare time, he reads, paints, builds his own gaming computers and utilizes the power of social media to share his passion for nature with hundreds of thousands of people.

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